Generate Images from Lines 室内设计生成器 by Junming Chen

Generate Images from Lines 室内设计生成器 by Junming Chen is a highly esteemed winner of the very prestigious 2023 A' Design Award 铁奖 in 生成式、算法、参数化与人工智能辅助设计 Competition Category.

铁生成式设计· 2023

Generate Images from Lines 室内设计生成器

by Junming Chen

Client: Junming Chen

A' Design Award 铁奖 Winner in 生成式设计 Category

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Verified Award Winner

Verify Award Status for #150690

View at A' Design Award Press Release Award Badge

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The Design

About Generate Images from Lines 室内设计生成器

《线稿生成图像》是一套通过线稿创建室内设计效果图的人工智能系统。该系统基于改进的扩散模型,并采用由专业设计师收集与标注的两万余张室内设计图像进行训练。设计师只需输入手绘或数字线稿,并选择装饰风格,如现代、日式、欧式或中式,即可在数秒内生成效果图。设计方案通过编辑线稿即可修改,无需手动建模与重新渲染。

The Recognition

About the A' Design Award 铁奖

Generate Images from Lines 室内设计生成器是 A' Design Award 铁奖得主，这是授予满足人们对设计精良的创作所期待的专业与工业要求的优良设计的声望认可。铁奖得主展现出其创作者的高超技艺、高度专业化、专家级的理解力和创造能力。预计Generate Images from Lines 室内设计生成器将成为一件备受推崇、令人钦佩且被珍爱的创作，既实用又创新。这件赢得 A' Design Award 铁奖的设计整合了行业最佳实践，并拥有与专业知识和才华相结合的称职技术特性。Generate Images from Lines 室内设计生成器因其严谨而受到尊重，旨在提供有助于让世界变得更美好的生活品质改善。

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: The design was done by artificial intelligence (AI) in collaboration with designers. We trained an AI that professionally generates interior designs, which can generate interior designs with different decorative styles based on input line drafts. It solves the problem that the traditional design modification requires remodeling and rendering. It only takes a few seconds to generate a design using this method, and the efficiency of generation and modification is increased by dozens of times.
Dimensions & Packaging: Use artificial intelligence to cooperate with designers to generate designs with different decorative styles. The design area is 160 square meters, and the decoration styles include modern, Japanese, European, and Chinese styles.
Tags: Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Production Technology: The AI technology we use is our improved diffusion model technology. The typical defect of the diffusion model is that it cannot generate design according to specific "decorative style" and "space attribute," which is fatal for interior design. To this end, we re-collected and manufactured a data set containing more than 20,000 interior design renderings and data annotations and handed the data set to AI learning to generate an AI suitable for interior design. The AI can generate interior renderings specifying "decorative style" and "space attributes" by inputting line sketches.
Design Challenge: The challenge of this design is to build a professional interior design AI that generates designs of high quality and correct decor. To this end, we asked professional designers to collect and label tens of thousands of interior design images and then handed over the filtered data to AI for training. Make AI understand what is "decorative style," "spatial attributes," and "aesthetic attributes" and generate an interior design with a specified decorative style.
Research: Research Background: The interior design process could be more convenient, and the efficiency of design and modification could be higher.
Methods: We trained an AI for professional interior design and used AI to cooperate with people to generate interior designs of various decorative styles from line drawings.
Results: Using our AI, designers can obtain an interior design rendering every few seconds, efficiently generating and modifying designs.
Insights: Our method can quickly generate large batches of interior designs with specified decoration styles and spatial attributes, and the generated results can be changed by modifying the line draft. Design efficiency is improved by eliminating the need for manual modeling and rendering.
Inspiration: The traditional process of obtaining renderings for interior design is tedious and time-consuming. We use artificial intelligence (AI) to generate interior design, improve design efficiency, and explore new ways of human-computer collaborative design. Specifically, we trained an AI to create interior designs, which can quickly generate and modify designs in cooperation with humans. Changing the design does not require modifying the model and re-rendering, which improves design efficiency.
Project Duration: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Operation Flow: 1. Professional designers collect interior design images and mark and screen them.
2. Use the filtered data to train a professional interior design AI.
3. Designers use AI to design.
4. The designer inputs the hand-drawn or design line draft into AI to specify the decoration style.
5. AI generates the interior design of the specified decoration style.
6. The designer adjusts the line draft of the unsatisfactory part of the design and then regenerates the design.
7. After adjusting the line draft and generating it multiple times, a good design is obtained.